The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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Study Virginia ISP 1994 (Orchowsky, Merritt, & Browning, 1994) Maryland 2003 (Piquero, 2003) Clark Co NV 2005 (Wiebush et al., 2005) Denver CO 2005 (Wiebush et al., 2005) Research Design Quasiexperiment (matched pairs design) Quasiexperiment (matched pairs design) Randomized controlled trial with high attrition. Randomized controlled trial with high attrition. Population Adults 18 and over at high risk to community and in need <strong>of</strong> services. Adult probationers and parolees in program neighborhoods. High risk male juvenile parolees originally placed in specific correctional facility. High risk male juvenile parolees originally placed in specific correctional facility. Intervention 20:1 caseload. Weekly contact. Home visits, employment verification, collateral contacts, record checks. No explicit caseload or contact requirements. Intensive community probation: <strong>of</strong>ficers in neighborhood <strong>of</strong>fices and conducting home visits and curfew checks along with police <strong>of</strong>ficers. 18:1 caseload, 3.1 contacts per month average later reduced to 1. Drug treatment, education, home visits, house arrest,, reentry services, treatment linkages in community. 18:1 caseload, 3.1 contacts per month average later reduced to 1. Drug treatment, curfew, reentry services, treatment linkages in community. Comparison Routine probation. Average 68:1 caseload, monthly contact. Caseload and contacts not specified. Traditional probation/parole supervision. 35+:1 caseload, 1.9 contacts per month average, regular parole services. 35.1 caseload, 1.7 contacts per month average. Caseloads also reduced to allow access to services. Outcome Treatment group more likely to fail on arrests. Treatment group less likely to fail on arrests, slightly more likely to fail on technical violations. No difference in arrests. Treatment group less likely to fail on convictions, more likely on technical violations. Treatment group more likely to fail on arrest and convictions, less likely on technical violations. 205
Study Los Angeles CA 2005 (Zhang & Zhang, 2005) New Jersey ISSP 2005 (Paparozzi & Gendreau, 2005) Norfolk VA 2005 (Wiebush et al., 2005) Maryland PCS 2006 (Taxman, Yancey, & Bilanin, 2006) Research Design Randomized controlled trial with high attrition. Quasiexperiment (matched sample design) Randomized controlled trial with high attrition. Quasiexperiment (matched pairs design) Population Juveniles under court supervision, meeting risk factors for delinquency, drug use and school or family problems. Mixed youth and adult parolee sample – high risk/need. High risk male juvenile parolees originally placed in specific correctional facility. Mostly probationers and some parolees, high risk for recidivism. Intervention 25:1 caseload, increased frequency <strong>of</strong> contact, strong focus on education and ensuring access to social services. 20-25:1 caseload, treatmentfocused program. Drug treatment, employment assistance, public and family provide assistance. 15:1 caseload, 10 contacts per month average gradually decreasing. Drug treatment, education, home visits, reentry services, treatment linkage. 55:1 caseload, emphasis on nature and content <strong>of</strong> contacts. Officer facilitates behavior management: treatment and pro-social activity. Comparison 100-150:1, regular probation supervision. 75-85:1 caseload. Regular parole – also received services but less so. Caseload not specified. Regular parole, including services (less than treatment group). 100:1 caseload, regular probation/parol e supervision. Outcome Treatment group more likely to fail on technical violation but less likely on arrest after 6 months – eventually no difference. Treatment group more likely to fail on technical violation but less likely to be revoked for new conviction. Treatment group less likely to fail on arrests and convictions, more likely on technical violations. Treatment group less likely to fail on new arrests and violation warrants. 206
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University of Penn
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In memory of Edwar
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Janel McCaffrey and Knakiya Hagans,
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traditional practice, we find no ev
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Methodology .......................
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LIST OF FIGURES Figure 1.1: Effect
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intensity makes no difference to re
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isk of committing
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impact of probatio
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which perhaps suggests that ISP is
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program intended to reduce the stra
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supervision with probation
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3. To what extent do the risk/need
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Methods Scale (SMS: Farrington et a
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Types of Outcomes
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Description of met
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actual behavior. We analyze technic
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Treatment of quali
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treatment group, and those to the r
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Discussion of Resu
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were evaluated in the same report (
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direction of effec
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To what extent does program philoso
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Which other components of</
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.450; technical violations: Q B < .
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it should be noted that those progr
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up in unpublished reports than thos
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violations first went before a judg
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2 One U.S. estimate indicates that
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Tables Table 1.1: Characteristics <
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Table 1.3: Moderator Variable <stro
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Table 1.4: Moderator Variable <stro
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Figures Figure 1.1: Effect
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Figure 1.5: Effect of</stro
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CHAPTER 2. ‘Low-Intensity
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What Works in Probation Supervision
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to do with it. Furthermore, the mor
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to the New York City and Oregon stu
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Barnes et al. (forthcoming) have su
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paradox.” He suggests that ‘not
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fatal shootings in Philadelphia are
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the proportions of
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Interventions and Follow-Up Probati
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officers more <str
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1. Does the effect of</stro
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all, resulting in a large number <s
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Differential treatment take-up and
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control group members who received
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effect of LIS on r
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incarcerated must also be removed f
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offenders in our s
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ecidivists in the sample, 77 commit
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(IRR = 1.41, p ≤ .107). SES did n
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probability of fai
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The count model ou
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estimate is also practically identi
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twice the risk of
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an end. On the other hand, research
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low-intensity supervision would imp
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Conclusion The aim
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We found that low-risk of</
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7 LIS participants who were transfe
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Tables Table 2.1: Sample Characteri
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Table 2.3: Frequency of</st
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Table 2.5: Instrumental Variables M
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Table 2.7: Prevalence of</s
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Table 2.9: Time to Failure (Violent
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Table 2.12: Treatment Effect by Sub
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Table 2.14: Frequency of</s
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Table 2.16: Instrumental Variables
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Figures Figure 2.1: Risk-Based Allo
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Figure 2.5: Survival Time for LIS E
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CHAPTER 3. Risk Prediction for Effe
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sensitivity of the
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Programs should be designed to adhe
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weight information in an appropriat
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statistical model that would predic
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The Philadelphia m
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assignment pool. Backfill probation
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Little research has been done on th
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already predicted to be at low risk
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It assumes that if of</stro
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involved. Crimes that obviously met
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We examine the potential interactio
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Page 171 and 172: obberies. The only
Page 173 and 174: of low-intensity s
Page 175 and 176: classified as low risk. The
Page 177 and 178: All the risk ratios in Table 3.9 in
Page 179 and 180: 0.55. Raising the threshold results
Page 181 and 182: are partly selected on the basis <s
Page 183 and 184: make up the majority of</st
Page 185 and 186: strategy allows probation o
Page 187 and 188: Notes 1 In this study, murder, atte
Page 189 and 190: Table 3.2: Sample Characteristics (
Page 191 and 192: Table 3.6: Predictive Ability at Al
Page 193 and 194: Table 3.9: Post-Random Assignment O
Page 195 and 196: APPENDICES Appendix A: Systematic R
Page 197 and 198: combination. The s
Page 199 and 200: B. ELIGIBILITY CHECKLIST B1. First
Page 201 and 202: Other: txcxloth C6d. Additional pro
Page 203 and 204: D. SAMPLE LEVEL CODING SHEET Instru
Page 205 and 206: E. DEPENDENT VARIABLE CODING SHEET
Page 207 and 208: F14. Comparison group sample size f
Page 209 and 210: weight w is then recalculated (6),
Page 211 and 212: Study Sheffield (Males) 1976 (Folka
Page 213 and 214: Study Dallas TX 1992 (Turner & Pete
Page 215 and 216: Study Minnesota ISR 1995 (Deschenes
Page 217 and 218: Study Clark WA 2003 (Barnoski, 2003
Page 219: Study Whatcom WA 2003 (Barnoski, 20
Page 223 and 224: Fed. Prob., 56, 12-17. Turner, Pete
Page 225 and 226: Study Reference Benekos & Sonnenber
Page 227 and 228: Study Reference Giblin (2002) Using
Page 229 and 230: Study Reference Lasater et al. (n.d
Page 231 and 232: Study Reference Robertson (2000) Co
Page 233 and 234: Study Reference Turner & Greene (19
Page 235 and 236: Appendix E: Philadelphia APPD Low-<
Page 237 and 238: Prevalence of Reci
Page 239 and 240: Frequency of Recid
Page 241 and 242: Instrumental Variables Model: Preva
Page 243 and 244: Instrumental Variables Model: Preva
Page 245 and 246: Post-RA Months in Jail and Probabil
Page 247 and 248: Scaled Schoenfeld Residuals Time =
Page 249 and 250: BIBLIOGRAPHY Chapter 1 ** Denotes t
Page 251 and 252: Cook, T. D., & Campbell, D. T. (197
Page 253 and 254: Glaze, L. E, & Bonczar, T. P. (2009
Page 255 and 256: MacKenzie, D. L. (2006a). What work
Page 257 and 258: Petersilia, J., Turner, S., & Desch
Page 259 and 260: safety first: 13 strategies for suc
Page 261 and 262: Wilson, D. B. (2010). Meta-analysis
Page 263 and 264: Angrist, J. D. (2006). Instrumental
Page 265 and 266: Clear, T. R., & Hardyman, P. L. (19
Page 267 and 268: period266.pdf Lowenkamp, C. T., Lat
Page 269 and 270: Rosch, J. (2006). Deviant peer cont
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Taxman, F. S., & Thanner, M. (2006)
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statistical learning. Journal <stro
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Federal Bureau of
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Marsh, K., & Fox, C., (2008). <stro
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Sherman, L. W. (1993). Defiance, de
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